Changes and Mechanisms of Long-Lived Warm Blobs in the Northeast Pacific in Low-Warming Climates

Cong Tang aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China
eCollege of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

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Jian Shi aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China
eCollege of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

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https://orcid.org/0000-0002-8042-7789
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Yu Zhang aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Shengpeng Wang aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Chun Li aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China
eCollege of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

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Riyu Lu cState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
dCollege of Earth and Planetary Sciences, University of the Chinese Academy of Sciences, Beijing, China

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Tengfei Yu aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China
eCollege of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

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Ruiqi Wang aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China
eCollege of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

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Ziyan Chen aFrontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, China
bQingdao National Laboratory for Marine Science and Technology, Qingdao, China
eCollege of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

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Abstract

In the last decade, three persistent warm blob events (2013/14, 2015, and 2019/20) in the northeast Pacific (NEP) have been hotly debated given their substantial effects on climate, ecosystems, and the socioeconomy. This study investigates the changes of such long-lived NEP warm blobs in terms of their intensity, duration, structure, and occurrence frequency under Shared Socioeconomic Pathway (SSP) 119 and 126 low-warming scenarios of phase 6 of the Coupled Model Intercomparison Project. Results show that the peak timing of the warm blobs shifts from the cold season to boreal summer. For the summer-peak warm blobs, their maximum intensity increases by 6.7% (10.0%) under the SSP119 (SSP126) scenario, but their duration reduces by 31.0% (20.4%) under the SSP119 (SSP126) scenario. In terms of their vertical structure, the most pronounced temperature signal is located at the surface, and their vertical penetration is mostly confined to the mixed layer, which becomes shallower in warming climates. Based on a mixed layer heat budget analysis, we reveal that a shoaling mixed layer depth plays a dominant role in driving the stronger intensity of the warm blobs under low-warming scenarios, while the stronger magnitude of ocean heat loss after their peaks explains the faster decay and thus shorter duration. Regarding occurrence frequency, the total number of the warm blobs does not change robustly in the low-warming climates. Following the summer peak of the warm blobs, extreme El Niño events may occur more frequently under the low-warming scenarios, possibly through stronger air–sea coupling induced by tropical Pacific southwesterly anomalies.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jian Shi, shijian@ouc.edu.cn

Abstract

In the last decade, three persistent warm blob events (2013/14, 2015, and 2019/20) in the northeast Pacific (NEP) have been hotly debated given their substantial effects on climate, ecosystems, and the socioeconomy. This study investigates the changes of such long-lived NEP warm blobs in terms of their intensity, duration, structure, and occurrence frequency under Shared Socioeconomic Pathway (SSP) 119 and 126 low-warming scenarios of phase 6 of the Coupled Model Intercomparison Project. Results show that the peak timing of the warm blobs shifts from the cold season to boreal summer. For the summer-peak warm blobs, their maximum intensity increases by 6.7% (10.0%) under the SSP119 (SSP126) scenario, but their duration reduces by 31.0% (20.4%) under the SSP119 (SSP126) scenario. In terms of their vertical structure, the most pronounced temperature signal is located at the surface, and their vertical penetration is mostly confined to the mixed layer, which becomes shallower in warming climates. Based on a mixed layer heat budget analysis, we reveal that a shoaling mixed layer depth plays a dominant role in driving the stronger intensity of the warm blobs under low-warming scenarios, while the stronger magnitude of ocean heat loss after their peaks explains the faster decay and thus shorter duration. Regarding occurrence frequency, the total number of the warm blobs does not change robustly in the low-warming climates. Following the summer peak of the warm blobs, extreme El Niño events may occur more frequently under the low-warming scenarios, possibly through stronger air–sea coupling induced by tropical Pacific southwesterly anomalies.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jian Shi, shijian@ouc.edu.cn

1. Introduction

In recent years, warm blobs in the northeast Pacific (NEP), also known as long-lived marine heatwaves (MHWs; Amaya et al. 2020; Bond et al. 2015; Chen et al. 2021a), have exerted substantial impacts on weather and climate (Hartmann 2015; Liu et al. 2021; Seager et al. 2015; Walsh et al. 2017), as well as the environment, ecosystems, human health, and the economy (e.g., Cavole et al. 2016; Jones et al. 2018; McCabe et al. 2016; Piatt et al. 2020; Whitney 2015). For example, during 2013–16, the NEP basin experienced a record-breaking extreme warm blob event, attracting wide attention among research communities (Di Lorenzo and Mantua 2016; Gentemann et al. 2017; Hu et al. 2017; Joh and Di Lorenzo 2017). Recently, another persistent warm blob has been observed over the NEP from the spring of 2019 to the end of 2020 (Amaya et al. 2020; Scannell et al. 2020; Chen et al. 2021b). Instead of the above case studies of the warm blobs, Chen et al. (2021a) and Tang et al. (2021) statistically identified long-lived (longer than 5 months) warm and cold blobs in the NEP based on observational data and showed their potential linkages with El Niño–Southern Oscillation (ENSO). In particular, Chen et al. (2021a) classified the warm blobs during 1951–2018 into single-peak and double-peak types, the latter featuring longer duration and stronger intensity. Given the frequent occurrence of the long-lived warm blobs in the NEP in the recent decade, their potential changes in warming climates are worth being investigated.

Recent studies investigated the projected changes of MHWs, which vary on synoptic-to-intraseasonal time scales (Hobday et al. 2016), shorter than interannual variability of the long-lived warm blobs (e.g., Liang et al. 2017; Chen et al. 2021a). For example, Oliver et al. (2018) reported that global extreme MHWs had increased in terms of frequency and duration during 2000–16 relative to 1982–98 based on observations. Laufkötter et al. (2020) revealed that the duration and intensity of some well-known MHWs, including the above 2013–16 NEP warm blob, will enhance more than twentyfold in the future as a result of anthropogenic climate change under a radiative forcing of 2.6 or 8.5 W m−2 from daily outputs of phase 5 of the Coupled Model Intercomparison Project (CMIP5). As for seasonal anomalous events of sea surface temperature (SST), Joh and Di Lorenzo (2017) reported that the NEP winter (January–March) oceanic temperature extremes will increase in amplitude, area, and frequency under high radiative forcing (8.5 W m−2) using the simulations from Community Earth System Model–Large Ensemble Community Project (CESM-LENS). They further suggested that the robust coupling between the winter North Pacific Gyre Oscillation (NPGO; Di Lorenzo et al. 2008) and the following winter Pacific decadal oscillation (PDO; Mantua et al. 1997; Zhang et al. 2018) can lead to prolonged warm anomalies over the NEP. While the projected changes of MHWs under global warming were extensively investigated, changes of the long-lived warm blobs have not been documented yet.

Additionally, the abovementioned studies on the projected changes of MHWs or temperature extremes were mostly based on high-level warming scenarios, while few documented the changes under low-level radiative forcings of 1.9 and 2.6 W m−2. These low-level radiative forcings, corresponding to limiting global warming under 1.5° and 2.0°C above preindustrial levels (UNFCCC 2015), are considered important for their lower challenges to the adaptation of climate change (King et al. 2017; O’Neill et al. 2017; Nangombe et al. 2018; Zhang et al. 2020; Zhao et al. 2020). Moreover, the results based on one single model, such as the CESM-LENS in Joh and Di Lorenzo (2017), should be evaluated from the perspective of multimodel ensemble. Hence, in this study, we aim to shed light on the potential changes of the long-lived warm blobs in the NEP and their underlying mechanisms under low levels of global warming at 1.5° and 2.0°C (i.e., 1.9 and 2.6 W m−2 radiative forcings) based on the state-of-the-art models from the CMIP phase 6 (CMIP6; O’Neill et al. 2016).

The rest of the paper is organized as follows. Section 2 presents the data and methods. Section 3 analyzes the changes of the warm blob properties between two stable periods of historical and low-warming simulations in terms of their intensity, duration, and three-dimensional spatial pattern. Then, this section investigates the associated atmospheric circulation anomalies and heat budget evolution to clarify the mechanisms responsible for the summer-peak warm blob changes. Finally, the major findings of this study are summarized in section 4 with our discussion.

2. Data and methods

a. Data

We use both historical and warming simulations from the CMIP6 to investigate changes of the long-lived warm blobs. For the warming simulations, the CMIP6 provides multimodel climate projections, classified by Shared Socioeconomic Pathways (SSPs), which are developed from the representative concentration pathways (RCPs) that describe a set of alternative trajectories for the atmospheric concentrations of key greenhouse gases (O’Neill et al. 2016). For example, the SSP119, SSP126, and SSP245 scenarios approximately follow the RCP1.9, RCP2.6, and RCP4.5 pathways with radiative forcings of 1.9, 2.6, and 4.5 W m−2, respectively. In particular, the SSP119 and SSP126 scenarios correspond to the goals of limiting global warming under 1.5° and 2.0°C above the preindustrial level (UNFCCC 2015), both of which are closer to the future target and important for lower risks of economy and human health. Therefore, we employ the models under the SSP119 and SSP126 scenarios (Fig. 1a), which are 9 models for SSP119 (names with bold fonts in Fig. 1a) and 22 models for SSP126, respectively. We use variables of SST, sea level pressure (SLP), surface winds, net surface heat flux, and ocean 3D temperature from the models’ first member (i.e., r1i1p1f1) of the historical and warming simulations. The ocean 3D temperature and heat flux outputs are interpolated onto the grids of Global Ocean Data Assimilation System (GODAS) from the National Centers for Environmental Prediction (NCEP) (Saha et al. 2006) to keep consistency among models. The resulting horizontal resolution is 1° × 1° with meridional resolution gradually getting finer to 1/3° between 10°S and 10°N, and vertical resolution is 10 m from surface to 240-m depth. Other variables are interpolated onto the grids of 1° × 1° horizontal resolution.

Fig. 1.
Fig. 1.

(a) Monthly standard deviation (STD; °C) of SST anomalies over the study area in the historical simulations of 22 CMIP6 models (names shown on the right) and observations (i.e., the mean value of ERSST v5 and HadISST v1.1) from 1925 to 1974 after removing the linear trend. The correlation coefficients between each model and the observation are also shown on the right, with a significant correlation at the 0.05 significance level denoted in black colors selected for analysis of the SSP126 scenario. Bold fonts represent the 9 models involved in both the SSP119 and SSP126 scenarios with 7 models in bolded black used for analysis of the SSP119 scenario. The 5% (dashed) and 95% (solid) lines after sorting the difference of STD (°C) of SST anomalies between the warming scenarios and historical run over (135°–160°W, 40°–50°N) for the 500 times calculation for (b) 9 SSP119 models and (c) 22 SSP126 models as a function of ensemble size.

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

To select the models with a better performance in depicting the SST seasonality over the study area (135°–160°W, 40°–50°N), we employ observational monthly SST data from the National Oceanic and Atmospheric Administration (NOAA) Extended Reconstructed Sea Surface Temperature version 5 (ERSST v5) with a 2° × 2° horizontal resolution (Huang et al. 2017) and the Hadley Centre Global Sea Ice and Sea Surface Temperature version 1.1 (HadISST v1.1) with a 1° × 1° horizontal resolution (Rayner et al. 2003). These two datasets were used for detecting the historical long-lived warm and cold blobs over the NEP (Chen et al. 2021a; Tang et al. 2021).

b. Model selections in the CMIP6

Following the methodology of Planton et al. (2018), we select the models used in the following analyses when the correlations of time series of monthly STD of SST anomalies averaged over the study area between historical simulations and observations (mean value of ERSST v5 and HadISST v1.1) during 1925–74 are significant at 0.05 significance level (Fig. 1a). This selection criterion ensures that the models are able to capture the seasonality of SST anomalies associated with the warm blobs in the NEP. Based on the criterion, 7 of the 9 models under SSP119 scenario and 15 of the 22 models under SSP126 scenario are selected, respectively (Fig. 1a).

To examine whether the number of the selected models is sufficient to investigate the response of SST variability to the low-level warmings, we employ the methodologies of Li et al. (2009) as well as Li and Wu (2013). We calculate the difference of annual-mean STD of SST anomalies between the warming and historical simulations for each model, and then average the difference over the study area for randomly choosing N models (Figs. 1b,c). Then, we repeat the above procedure for 500 times, sort the generated values, and determine their 5% and 95% percentiles. The result does not change significantly when the procedure repeats 1000 times. The minimum ensemble size is determined when the 5% and 95% percentiles are in the same sign. By this definition, the minimum ensemble sizes are 7 for SSP119 models (Fig. 1b) and 12 for SSP126 models (Fig. 1c), both of which are within the numbers of the corresponding selected models. This result suggests that the number of the selected models (Fig. 1a) is enough for the following analyses.

Previous studies showed that under the SSP119 and SSP126 scenarios, the rising of global-mean surface air temperature will become stable by 2050 (O’Neill et al. 2016; Zhang et al. 2021). We find that the case is also true for SST (Fig. 2a). Therefore, a future period of 2051–2100 is selected for the following analyses. For comparison, a relatively stable 50-yr historical period over 1925–74 is used (Fig. 2a). Nevertheless, the linear trends during 2051–2100 and 1925–74 are removed for all the variables because we mainly focus on the role of SST variability, rather than the mean state, in affecting properties of the warm blobs, such as the amplification of the seasonal cycle (Fig. 2b). To this end, the monthly anomalies in both historical and warming periods are calculated by removing the climatological monthly mean of the historical scenario over 1925–74. Note that the period of observational data used also ranges from 1925 to 1974 (Fig. 1a), consistent with the analysis period in the historical simulations.

Fig. 2.
Fig. 2.

(a) Ensemble-mean annual-mean SST (°C) of the study area (135°–160°W, 40°–50°N) in the historical run (black line for SSP126 scenario and blue dashed line for SSP119 scenario), SSP119 (green dashed line), and SSP126 (pink line) scenarios, respectively. Shading indicates 0.75 STD spread. The warming temperature between 2051–2100 and 1925–74 for SSP119 (green) and SSP126 (red) scenario is shown in bottom-right corner. The two gray vertical lines indicate the boundary years of 1975 and 2050, respectively. (b) As in (a), but for the seasonal cycle of SST (°C) over the study area after removing the corresponding linear trends.

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

c. Definitions of the blob index and warm blob event

According to Tang et al. (2021) and Chen et al. (2021a), a monthly blob index is defined as SST anomaly within the study area normalized by its STD in the historical scenario. A warm blob event is identified when the blob index is greater than 0.75 and lasts for at least 5 months. The threshold of 0.75 is to obtain sufficient case numbers of the long-lived warm blobs. The peak (mean) intensity is the maximum (mean) blob index during the lifetime of a warm blob event. The duration is the number of months during a warm blob case. The accumulated intensity is calculated as the accumulation of the blob index during the lifetime of a warm blob event.

d. A mixed layer heat budget analysis

Following Cronin et al. (2015) and Chen et al. (2021a,b), we utilize a simplified mixed layer heat budget analysis for the study of the warm blobs formulated as
ρCpTt=Qneth+residual,
where T is the temperature averaged over the mixed layer, T/t is the rate of the temperature change (i.e., the temperature tendency term), and ρCp is the volumetric heat capacity of seawater with a value of 4.088 × 106 J °C−1 m−3. The terms on the right-hand side (rhs) of Eq. (1) denote net heat flux term at ocean–atmosphere interface and residual processes, respectively. The net surface heat flux (Qnet; positive downward) includes net shortwave radiation, net longwave radiation, net sensible heat flux, and net latent heat flux; h indicates the monthly mixed layer depth (MLD), defined as the depth where the temperature difference with respect to the surface is equal to 0.2°C (Thompson 1976; de Boyer Montégut et al. 2004). The residual processes comprise of oceanic horizontal advection within the mixed layer and vertical entrainment and diffusion at the bottom of the mixed layer. The anomalies of surface heat flux and residual terms are calculated to explain the rate of change of temperature anomalies. In this study, we consider the oceanic processes as residual term due to the lack of data in the selected models. Moreover, some of the selected models do not provide ocean temperature and heat flux data (see Table 1), leading to the decrease of case numbers of the warm blobs (Figs. 7, 9, and 10). Further details on the heat budget analysis can be referred to Cronin et al. (2015).
Table 1

The number of the long-lived warm blobs from 15 selected CMIP6 models in historical (1925–74), SSP119 (2051–2100), and SSP126 (2051–2100) scenarios. Parentheses and square brackets indicate that net surface heat flux and seawater potential temperature are not provided by the models, respectively.

Table 1
To quantify the relative contributions of surface heat flux and MLD anomalies to the temperature tendency, we further decompose the surface heat flux term as follows, according to Alexander and Penland (1996), Amaya et al. (2020, 2021), and J. Shi et al. (2022):
(Qh)Qh¯Q¯hh¯2(QhQh¯h¯2),
where Q represents Qnet. The first term on the rhs (Q1) indicates the contribution of surface heat flux anomalies (Q′). The second term on the rhs (Q2) denotes the contribution of MLD anomalies (h′). The third term on the rhs represents the nonlinear interaction between Q′ and h′; however, its contribution was suggested to be limited (J. Shi et al. 2022) and thus is neglected in this study.

3. Results

a. Frequency, intensity, and duration changes of the warm blobs in the NEP

To understand the temperature variability over the NEP, we first show the time series of annual-mean SST in the study area (Fig. 2a). Similar to the evolution of global-mean surface air temperature (e.g., Zhang et al. 2021), SST during the warming period (1975–2050) exhibits a significant warming trend but becomes quasi-equilibrium during the reference period (1925–74) and future period (2051–2100) (Fig. 2a). The 50-yr-mean SSTs over 2051–2100 within the study area under the global warming of 1.5° and 2.0°C scenarios are about 1.4° and 1.8°C higher than that under the historical scenario averaged over 1925–74, respectively (Fig. 2a). To reveal the amplitude of SST seasonal cycle over the study area, we further calculate the climatological monthly mean SST averaged over 1925–74 for the historical run and 2051–2100 for the warming scenarios, respectively (Fig. 2b). The multimodel mean seasonal cycles under the low radiative forcing levels display larger amplitude than those of the historical period; however, this difference is not statistically significant at 0.1 significance level. In addition, we do not probe into the slightly stronger amplitude of SSP119 scenario than that of SSP126 scenario due to their difference in model numbers.

According to the observational analyses of Chen et al. (2021a), the long-lived warm blobs in the NEP occur 1.6 times per decade with an average duration of 9.7 months during 1951–2018. Most recently, the 2019/20 warm blob experienced a 20-month duration as the most persistent case since 1951 (Chen et al. 2021b). Thus, we first calculate the number of the long-lived warm blobs events in different models and scenarios (Table 1) as well as observational data over the same period (i.e., 1925–74). For the ensemble-mean, the frequency of the warm blobs over the NEP in the historical scenario is approximately 1.6 times per decade (Table 1), slightly fewer than the observed frequency (2.0 times per decade) during 1925–74 but equal to that during 1951–2018 (Chen et al. 2021a). The frequency of the warm blobs is 1.2 and 1.5 times per decade under the 1.5° and 2.0°C warming scenarios, respectively. This slight difference from historical scenario is not statistically significant, partly due to the large deviation of different models (Table 1). In brief, it is projected that the frequency of the long-lived warm blobs over the NEP under the 1.5° and 2.0°C warming scenarios may not change significantly.

Next, we investigate the changes in intensity of the warm blobs under the warming scenarios. The ensemble-mean peak intensity (Fig. 3a) and mean intensity (Fig. 3b) are higher under the 1.5° and 2.0°C warming scenarios than that in the historical scenario, consistent with the results of Laufkötter et al. (2020) that were based on a radiative forcing of 2.6 or 8.5 W m−2 from CMIP5. In detail, the peak (mean) intensity of the warm blobs has a significant increase by 9.4% (9.3%) under 1.5°C warming scenario, around 1.9 (1.3) in terms of the dimensionless blob index (Figs. 3a,b). When global warming follows the SSP126 trajectory, the increasing rates are 9.3% for the peak intensity and 10.2% for the mean intensity, respectively, similar to those of SSP119 scenario (Figs. 3a,b). Specifically, the larger increase of the mean intensity under the SSP126 scenario is because its historical value is lower than that of the SSP119 scenario (Fig. 3b). For comparison, the peak and mean intensities of the warm blobs are close to observations (about 1.6 and 1.2, respectively) computed over the same period (i.e., 1925–74) (Figs. 3a,b).

Fig. 3.
Fig. 3.

The (a) peak intensity, (b) mean intensity, (c) duration (month), and (d) accumulated intensity of the long-lived warm blobs in historical (light gray for SSP119 while dark gray for SSP126), SSP119 (pink), and SSP126 (red) scenarios for individual models and ensemble mean. Note that the intensity in (a), (b), and (d) is dimensionless due to the normalization process to the blob index. The black dashed line denotes the corresponding statistics in observations (i.e., the mean value of ERSST v5 and HadISST v1.1) over 1925–74. The red (blue) value represents the increase (decrease) magnitude of ensemble mean of warming scenarios relative to the historical scenario, with the triangle and rhombus indicating a significant difference at the 0.1 and 0.05 significance level of Student’s t test, respectively. The star indicates a robust change with more than 2/3 of involved models (5 for SSP119 or 10 for the SSP126 scenario) agreeing on the sign of change (Zhang et al. 2021).

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

In terms of duration, the long-lived warm blobs lasted 8.2 (8.9) months on average under the historical simulation of SSP119 (SSP126) scenario, longer than the 7.1 months in observations during 1925–74 and the 8 months in observations during 1951–2018, documented in Chen et al. (2021a). However, the duration of the warm blobs becomes robustly shorter, at 7.2 and 7.3 months, under the SSP119 and SSP126 warming scenarios, respectively (Fig. 3c). Therefore, the accumulated intensity of the warm blobs becomes weaker under the two warming scenarios (Fig. 3d) due to the dominant effect of duration (Fig. 3c). In particular, the accumulated intensity under the 2.0°C warming scenario significantly decreases by 12.8%. The accumulated intensities are 9.4 and 9.5 (dimensionless) under the SSP119 and SSP126 warming scenarios, respectively (Fig. 3d).

To explain the stronger intensity but shorter duration of the warm blobs, we first inspect their changes in seasonality (Fig. 4) and changes in seasonal cycle (Fig. 2b). The warm blobs are more likely to occur in boreal winter and spring (Figs. 4a,b) but become more frequent from June to September in the warming scenarios (Figs. 4a,b). In view of the timing of the peak months, the warm blobs tend to peak in cold season such as November, February, and May in the historical simulations (Figs. 4c,d), in accordance with Chen et al. (2021a). By contrast, the peak months shift to boreal summer in the low-warming climates (Figs. 4c,d). At this time, the warm blob cases peaking in winter become much fewer.

Fig. 4.
Fig. 4.

The probability of all months within the duration of the NEP warm blobs in (a) historical (blue) and SSP119 (green) scenarios and (b) historical (gray) and SSP126 (pink) scenarios. (c),(d) As in (a) and (b), but for peak months of the warm blobs.

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

Since more warm blob cases peak in summer in the low-warming climates (increase by 1.2 and 6.0 per decade under the SSP119 and SSP126 scenarios, respectively), in the following we only investigate the ensemble-mean of the summer-peak warm blobs. Figure 5a shows that the warm blobs intensify robustly by 6.7% and 10.0% in terms of the peak intensity for the SSP119 and SSP126 scenarios, respectively. Similarly, their mean intensity increases significantly by 13.3% and 16.8% in the SSP119 and SSP126 scenarios, respectively (Fig. 5b). Their duration drops to about 6 months, more dramatically compared to that of all the warm blobs involved (Fig. 3c) with 31.0% for the SSP119 scenario and 20.4% for the SSP126 scenario (Fig. 5c). The shorter duration of the warm blobs may reflect the decline in ocean memory over the twenty-first century (H. Shi et al. 2022). In addition, the accumulated intensity of the warm blobs does not exhibit significant changes in the low-warming climates (Fig. 5d). In the following analyses, we focus on the warm blobs peaking in summer due to the sufficient case number and illustrate their spatiotemporal features and underlying mechanisms during their evolution.

Fig. 5.
Fig. 5.

As in Fig. 3, but only ensemble means of the warm blobs peaking in summer. The case number for the ensemble mean is 17 for the historical scenario of SSP119, 23 for the SSP119 scenario, 28 for the historical scenario of SSP126, and 58 for the SSP126 scenario.

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

b. Changes of three-dimensional structure of the warm blobs

Figure 6 shows the composite evolution of anomalous SST patterns from the summer peak of the warm blobs. Here, the peak month denotes the month when the blob index is largest. In line with Fig. 5, SST anomalies over the study area are stronger in the warming scenarios, with similar patterns near the study area compared to the historical run (Figs. 6a,e,i,m). The SST anomalies extend westward into the northwest Pacific under both 1.5° and 2.0°C warming conditions. In the North Pacific, the basin-scale SST pattern resembles the negative phase of the NPGO (Joh and Di Lorenzo 2017) (Figs. 6a,e,i,m). The negative SST anomalies in the western subtropical Pacific become weaker under the warming conditions at the peak time of the warm blobs (Figs. 6e,m), and exhibit distinct features compared to the prominent positive anomalies around the Gulf of Alaska (GOA). The warm blobs decay in the following 3 months (Figs. 6b,f,j,n). At 6 months after the peak, they become much weaker in the historical scenarios (Figs. 6c,k) or disappear and are replaced by negative SST anomalies in the warming scenarios (Figs. 6g,o), confirming the shorter duration of the warm blobs in the low-warming climates.

Fig. 6.
Fig. 6.

The composite SST anomalies (shading; °C) at the (a),(e),(i),(m) peak month and following (b),(f),(j),(n) 3; (c),(g),(k),(o) 6; and (d),(h),(l),(p) 9 months of the warm blobs peaking in summer for the historical SSP119, SSP119, historical SSP126, and SSP126 scenarios, respectively. The green boxes indicate the study area. Stippling indicates exceeding the 0.1 significance level based on the Student’s t test. The red contour outlines the 0.5°C SST anomalies. The case number for composites is 17 in (a)–(d), 23 in (e)–(h), 28 in (i)–(l), 58 in (m) and (n), 57 in (o), and 56 in (p).

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

It has been documented that the warm blobs in the NEP may interact with ENSO variability (e.g., Capotondi et al. 2019; Chen et al. 2021a; Xu et al. 2021). The results show that the warm anomalies stretch from the study area into the tropics through the subtropical area at the peak month of the warm blobs, implying a potential linkage with ENSO (Figs. 6a,e,i,m). Importantly, we find an intensified El Niño–like signature in the tropical Pacific 6 months after the summer peak under the warming scenarios (Figs. 6g,o versus Figs. 6c,k). Note that the El Niño–like warming signal is located over both the central and eastern tropical Pacific (Figs. 6g,h,o,p). Similar linkage between warm anomalies over the NEP and El Niño–like warming has been reported by Hartmann (2015) and Chen et al. (2021a). To quantitatively depict the potential connection between El Niño and the NEP warm blobs, we calculate the probability of El Niño events in boreal winter (November to January) after the summer-peak warm blobs (Table 2). Here, an El Niño event is identified when the 3-month-mean (November–January) Niño-3.4 index (i.e., the SST anomalies averaged over 5°N–5°S and 170°–120°W) is larger than 0.5°C. In detail, the probability increases from 29.4% (39.3%) in the historical scenario to 52.2% (48.3%) in the SSP119 (SSP126) scenario (Table 2). However, the probability difference between the historical and warming scenarios is not statistically significant at 0.1 significance level. Moreover, the probability of El Niño events in winter largely increases when the NEP warm blobs occur and reach their peak in the preceding summer (Table 2 versus Table S1 in the online supplemental material). In terms of the intensity, however, the changes of the peak intensity for El Niño events after the summer peak of the warm blobs significantly increase by 67.2% (exceeding 0.05 significance level) and 15.1% in the SSP119 and SSP126 warming scenarios, respectively. Accordingly, we further classify El Niño events into different intensity categories and compute the corresponding occurrence probability (Table 2). Extreme (maximum intensity larger than 1.5°C) El Niño events become significantly more frequent from 0 in the historical run to 26.1% in the SSP119 scenario while there are around twofold of the values between the SSP126 and historical runs (Table 2). Similarly, strong (maximum intensity larger than 1.0°C) El Niño events also occur more frequently from 11.8% in the historical run to 34.8% in the SSP119 scenario (Table 2). Note that the number of the models is sufficient for the ENSO analysis (Fig. S1) considering the uncertainty of future changes in El Niño (Collins et al. 2010). Therefore, the El Niño events with stronger intensity are more likely to occur in winter following the summer-peak NEP warm blobs in the low-warming climates. One possible mechanism is the seasonal footprinting mechanism (SFM; Vimont et al. 2001, 2003), in which subtropical warm SST anomalies associated with the warm blobs evolve into the tropical Pacific (Fig. 6). The detailed processes involved in this evolution are beyond the scope of this study.

Table 2

The probability of El Niño events in the following winter after the summer peak of the warm blobs in historical for SSP119, SSP119, historical for SSP126, and SSP126 scenarios. The maximum intensity of El Niño events larger than 1.0° and 1.5°C is classified into strong and extreme categories, respectively. Here * and *** indicate the difference exceeds the 0.1 and 0.01 significance levels based on Student’s t test. The case number is as in Fig. 5.

Table 2

To show the vertical structure of the summer-peak warm blobs, we plot the composite evolution of the temperature anomalies averaged over the study region (Fig. 7). The warmer-than-normal waters are strongest near the surface and weaken downward (Fig. 7). In the historical simulation, this feature is similar between 7 models with SSP119 (Fig. 7a) and 9 models with SSP126 (Fig. 7c), albeit with stronger signal for the former. The vertical penetration of warm anomalies can reach around 40 m, observed from the 0.5°C isotherm (Figs. 7a,c). Under the SSP119 scenario, the warmer waters become much stronger, but their vertical extent outlined by 0.5°C isotherm shrinks (Fig. 7b). The MLD is also significantly shallower from the leading 3 months to the peak (Fig. 7c), possibly associated with the decreased vertical penetration as the warm blobs are mostly stored within the mixed layer (Chen et al. 2021b). Moreover, Amaya et al. (2021) has reported the important role of MLD in affecting the MHW variation in a warming climate. After the peak, the warm anomalies decay more rapidly, denoted by the 0.5°C isotherm (Fig. 6b) compared to the corresponding historical run (Fig. 6a), the result consistent with the duration changes in Fig. 3c. In terms of the SSP126 scenario, the stronger warm anomalies (Fig. 7d) than those of the historical scenario (Fig. 7c) are significant, in accordance with Figs. 3a and 3b. But the differences in vertical extent, MLD, and decay rate between the SSP126 and historical scenarios are not robust (Fig. 7c versus Fig. 7d). In addition, the shallower MLDs during the warm blobs are clearer in other seasons because the MLD shoals in summer (Fig. S2).

Fig. 7.
Fig. 7.

The composite evolution of ocean temperature anomalies (shading; °C) and MLD (green dashed lines for the historical scenario and green solid lines for the warming scenario; m) of the warm blobs peaking in summer in the (a) historical for SSP119, (b) SSP119, (c) historical for SSP126, and (d) SSP126 scenarios from the leading 4 months to lagging 4 months relative to the peak month. Purple circles and green stars indicate the differences of temperature and MLD between warming and historical scenarios exceeding the 0.1 significance level of Student’s t test, respectively. The bottom-right corner shows the case number for composites is 17 in (a), 23 in (b), 18 in (c), and 35 in (d), respectively. Note the difference in case numbers is due to the missing data shown in Table 1 (see square brackets).

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

c. Atmospheric circulation changes associated with the long-lived warm blobs

To explain the changes of the long-lived warm blobs under the warming scenarios, we further inspect the atmospheric circulation anomalies associated with the summer-peak warm blob events. Figure 8 shows the composite evolution of SLP and surface wind anomalies relative to the summer peak of the warm blob events. In accordance with previous studies (e.g., Chen et al. 2021a), easterly anomalies in the study area weaken the prevailing westerly background (Figs. 8f–h), decreasing the ocean heat loss to the atmosphere via less evaporative cooling. The weakened westerly winds favor the shallower MLD (Fig. 7b) due to the weaker mechanical mixing. A North Pacific Oscillation (NPO)-like (Wallace and Gutzler 1981) SLP pattern is identified prior to the peak month (Figs. 8a,b,f,g,k,l,p,q), a meridional dipole with a positive center near Alaska and the GOA and a negative center over the midlatitude North Pacific. Consistent with the intensification of the warm blobs in the warming climates (Figs. 5 and 6), the easterly anomalies associated with the NPO-like pattern are much stronger, particularly 2 months before the peak (Figs. 8f,p versus Figs. 8a,k). After the peak month, the NPO-like signature gradually dissipates (Figs. 8d,e,i,j,n,o,s,t). Instead, the NEP near the study area is largely replaced by low pressure anomalies (Figs. 8i,s,t and Fig. S3) induced by an El Niño–like warming in the tropics (Fig. 6; Horel and Wallace 1981; Hoerling et al. 1997), which accelerates the termination of the warm blobs.

Fig. 8.
Fig. 8.

The composite SLP (shading; hPa) and surface wind (vectors; m s−1) anomalies by the (a),(f),(k),(p) leading 2 months; (b),(g),(l),(q) leading 1 month; (d),(i),(n),(s) lagging 1 month; and (e),(j),(o),(t) lagging 2 months relative to (c),(h),(m),(r) the peak of the warm blobs peaking in summer in the historical for SSP119, SSP119, historical for SSP126, and SSP126 scenarios, respectively. The green boxes indicate the study area. Stippling and vectors indicate the SLP and wind anomalies exceeding 0.1 significance level of Student’s t test. The number of the warm blobs for composite is 17 in (a)–(e), 23 in (f)–(j), 24 in (k)–(o), and 58 in (p)–(t). The difference in case numbers from that in Fig. 6 is due to the missing data in the CIESM model of the SSP126 scenario.

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

As mentioned above, the subtropical SST anomalies associated with the warm blobs (Fig. 6) imply the role of the SFM in triggering El Niño. The stronger NPO-like pattern under the low-warming scenarios, especially for the SSP119 scenario (Figs. 8f–h), which is crucial for the SFM (Vimont et al. 2001, 2003), further indicates the potential effect of the SFM on contributing to the El Niño development. The cyclonic anomalies in the southern lobe of NPO-like expression in the subtropical eastern Pacific are crucial parts in the evolution of El Niño (Fig. 8), as reported by previous studies (e.g., Su et al. 2018; Amaya 2019; Amaya et al. 2019). Under the two warming scenarios, the southwesterly anomalies over the tropical Pacific largely intensify from the peak in summer (Figs. 8h,i,j,r,s,t), possibly resulting from the excited summer deep convection response process in the vicinity of the climatological intertropical convergence zone (Amaya et al. 2019). The intensified southwesterly anomalies further give rise to the ENSO development by invoking the wind–evaporation–SST (WES) feedback (Xie 1999).

d. Underlying mechanisms responsible for the changes of the warm blobs

To reveal the mechanisms responsible for the intensity and duration changes of the warm blobs in the low-warming climates, we first illustrate the evolution of surface heat flux term [i.e., the first term on the rhs of Eq. (1)] in Fig. 9. For the SSP119 scenario, the magnitude of surface heat flux term within the study area is much larger 2 months before the summer peak (Fig. 9f versus Fig. 9a), benefiting the shallower MLD (Fig. 7b) by weakening buoyancy-driven mixing. Similarly, the surface heat flux term exhibits much larger magnitude at the leading 2 months and 1 month for the SSP126 scenario (Figs. 9p,q versus Figs. k,l). After the peak, the warm blobs attenuate more quickly under the warming scenarios due to the stronger cooling effect of the surface heat flux term (Figs. 9i,j,s,t). By contrast, the magnitude of the negative surface heat flux term within the study area is much smaller in the historical simulations (Figs. 9d,e,n,o), prolonging the lifetime of the warm blobs as shown in Fig. 5c.

Fig. 9.
Fig. 9.

As in Fig. 8, but for composite surface heat flux term (°C month−1) of the mixed layer heat budget [see Eq. (1)]. The case number for composite is 16 in (a)–(e), 21 in (f)–(j), 11 in (k)–(o), and 30 in (p)–(t), respectively. Note the difference in case numbers is due to the missing data shown in Table 1 (see parentheses and square brackets).

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

Next, we quantitatively compare the evolution of the temperature tendency with that of the surface heat flux term and residual term (i.e., oceanic processes; Fig. 10). The stronger intensity under the two warming scenarios corresponds to the larger rate of change of SST anomalies (black line) over the study area (Figs. 10b,d versus Figs. 10a,c). The surface heat flux term (red line) is the dominant factor for the intensification of the warm blobs under the SSP119 scenario (Fig. 10b). Its magnitude is much larger than that under the historical scenario (Fig. 10a) within the leading 3 months. As for the SSP126 scenario, the surface heat flux term is also the primary factor for the stronger intensity of the warm blobs than that of the historical scenario (Figs. 10c,d), consistent with Fig. 9. Moreover, oceanic processes (green line), estimated by the residual term, inhibit the development of the warm blobs (Figs. 10b,d). We do not dig into the oceanic advection and vertical entrainment in this study, limited by the data deficiency in the two low-level warming scenarios of CMIP6.

Fig. 10.
Fig. 10.

The composite evolution of temperature tendency (black), heat flux term (red), and residual (green) indicative of oceanic processes for the mixed layer heat budget (°C month−1) of the warm blobs peaking in summer in the (a) historical for SSP119, (b) SSP119, (c) historical for SSP126, and (d) SSP126 scenarios from the leading 4 months to lagging 4 months, respectively. Stars indicate the difference between warming and historical scenarios exceeding 0.1 significance level based on the Student’s t test. The case number is as in Fig. 9.

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

After the summer peak, the temperature tendency becomes negative, denoting the weakening of the warm blobs (Fig. 10). The magnitude of the temperature tendency is larger in the two warming scenarios (Figs. 10b,d) than that of the historical results (Figs. 10a,c). This acceleration of the warm blob dissipation leads to a shorter duration (Fig. 5c). In this stage, the surface heat flux term switches into negative, triggering the termination of the warm blobs in all the scenarios (Fig. 10). In addition, the larger cooling tendency under the two warming scenarios is due to the stronger magnitude of the negative surface heat flux term (red lines in Figs. 10b,d). Generally, the future property changes of the warm blobs in all four seasons (Fig. 3 and Fig. S4) can be mostly explained by the summer-peak ones (Figs. 5 and 10).

To illuminate the relative contributions of surface heat flux (Q′) and MLD anomalies to the surface heat flux term, we further decompose the surface heat flux term [see Eq. (2); Fig. 11]. Overall, the Q1 + Q2 terms can well capture the evolution of the surface heat flux term. Before the summer peak, the dominant effect of the surface heat flux term is mainly contributed by shoaling MLD anomalies (Figs. 7 and 11). Anomalous surface heating also promotes the development of the warm blobs with a secondary importance (Fig. 11). However, after the peak, stronger magnitude of the negative surface heat flux anomalies, indicative of more intense heat loss to the atmosphere, is the primary factor of the negative surface heat flux term (Fig. 11). At this time, the deepening MLD and thus negative Q2 can also induce the decay of the warm blobs (Figs. 11b,d).

Fig. 11.
Fig. 11.

As in Fig. 10, but for composite evolution of surface heat flux term (red line), Q1 (purple line), Q2 (green line), and Q1 + Q2 (orange line).

Citation: Journal of Climate 36, 7; 10.1175/JCLI-D-22-0152.1

4. Conclusions and discussion

Using the model outputs from CMIP6, this study explored the potential changes of the long-lived warm blobs in the NEP in the low-warming climates from the aspects of their intensity, duration, as well as horizontal and vertical structures. Based on the low-level radiative forcing scenarios (i.e., SSP119 and SSP126), we pointed out that the peak season of the NEP warm blobs shifts from boreal cold season to summer, while the occurrence frequency of the NEP warm blobs does not robustly change during the stable period (2051–2100) of the low-warming scenarios. For the summer-peak warm blobs, the peak intensity and mean intensity of the NEP warm blobs peaking in summer will enhance significantly, as shown in both SST and vertical temperature anomalies. Vertically, the most pronounced warming signal is located at the surface, with its vertical penetration shallower in the low-warming climates especially under the SSP119 scenario. Under the SSP119 scenario, the warm waters outlined by 0.5°C isotherm are around 30 m compared to 40 m in the historical scenario. Consistently, the MLD shoals sharply in response to the intensive warming over the study area. The warming signal related to the warm blobs is mostly concentrated within the mixed layer. Hence, although the lingering of heat below MLD can affect coastal waters (e.g., Jackson et al. 2018), the warm blob events can be generally viewed as a mixed layer phenomenon over the NEP (e.g., J. Shi et al. 2022). On the other hand, the duration of the warm blobs decreases under the low-level radiative forcings, especially for those peaking in summer. By applying a mixed layer heat budget, we concluded that the surface heat flux term is the dominant factor in explaining the evolution of the warm blobs. Specifically, shoaling MLD anomalies (i.e., Q2) is the major component of the positive surface heat flux term before the summer peak, leading to the stronger intensity of the warm blobs. Anomalous surface heating (i.e., Q1) also favors the development of the warm blobs with a secondary importance. However, the relative importance reverses at the decay phase of the warm blobs.

In comparison, Oliver et al. (2018) indicated that the MHWs have become the longer and more frequent over the past century based on reanalysis and observational data. Frölicher et al. (2018) also projected an increasing intensity and duration of MHWs over the NEP under both the 1.5° and 2.0°C warming conditions based on CMIP5 data. Their different results in frequency and duration from this study may be in part because 1) although the MHWs they identified can persist for a few months according to Hobday et al. (2016), they usually operate on synoptic to intraseasonal time scales; in contrast, the NEP warm blobs are long-lived events operating on interannual time scales (Liang et al. 2017; Chen et al. 2021a); 2) the changes of the warm blobs in this study are computed over a quasi-equilibrium period with linear trends removed, while the warmer mean state largely affects the metrics of MHWs in Frölicher et al. (2018) as they used the 99th percentile threshold of a fixed baseline; and 3) we employed monthly mean SSP119 and SSP126 outputs of CMIP6 while Frölicher et al. (2018) used daily mean RCP2.6 and RCP8.5 outputs of CMIP5. Recently, Wang et al. (2022) proposed that the intensified ocean seasonal cycle can escalate more destructive MHWs with larger cumulative duration (i.e., the product of mean duration and frequency) based on the RCP8.5 and SSP585 high radiative forcing scenarios. The difference between our study and Wang et al. (2022) may lie in the time scales of the MHWs and the warm blobs and the warming scenarios. Moreover, Joh and Di Lorenzo (2017) concluded that the NEP winter warm extremes will increase in frequency under the RCP8.5 scenario from CESM-LENS. The differences in model, season, and warming scenario may explain our difference in frequency with them.

We also highlight that the relationship between the summer-peak warm blobs in the NEP and El Niño is enhanced in the low-warming climates. The anomalous southwesterlies in the subtropical Pacific potentially related to the SFM become more prominent, initiating El Niño development via the WES feedback and summer deep convection response process (Amaya et al. 2019). Under the warming scenarios, more strong-to-extreme El Niño events are likely to occur in winter following the summer-peak warm blobs over the NEP basin, suggesting that the extratropical factor may be more important in the future ENSO prediction. Nevertheless, further investigations should be conducted through numerical modeling to understand the involved physical processes.

Note that although the case number becomes fewer when analyzing the atmospheric and oceanic subsurface characteristics (Figs. 710), the major findings in this study hold after setting the case number to be the same as that in Fig. 9 (see Tables S2–S3 and Figs. S5–S11). We do not further explore the changes of the warm blobs peaking in other seasons, limited by their small case number, which deserve in-depth investigation in the future. The question on how the NEP warm blobs change in a high-radiative forcing climate, such as SSP585 scenario, should also be explored. Although our results suggested that surface heat flux anomaly is crucial for the intensified warm blobs, the potential contributions of surface radiation (Myers et al. 2018) and turbulent heat flux are not clearly separated and thus investigated in this study. Moreover, as the cold blobs in the NEP exhibit distinct characteristics compared to the warm blobs (Tang et al. 2021), their potential changes in a warming climate should be evaluated, which may give implications on La Niña prediction.

Acknowledgments.

We sincerely thank the three anonymous reviewers for their constructive comments and suggestions. J.S. is supported by the National Natural Science Foundation of China (42006013), China Postdoctoral Science Funding (2021M693017), and Qingdao Postdoctoral Grant. C.L. is funded by the National Key R&D Program of China (2017YFA0603801). Y.Z. is supported by the Fundamental Research Funds for the Central Universities (202213050) and the project funded by China Postdoctoral Science Foundation (2021M703034).

Data availability statement.

The outputs from CMIP6 models are available at https://esgf-node.llnl.gov/. And SST data from ERSST v5 and HadISST v1.1 are downloaded from https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html and https://www.metoffice.gov.uk/hadobs/hadisst/data/download.html, respectively. The GODAS dataset from NCEP can be accessed from https://psl.noaa.gov/data/gridded/data.godas.html.

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    • Search Google Scholar
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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
  • Shi, H., and Coauthors, 2022: Global decline in ocean memory over the 21st century. Sci. Adv., 8, eabm3468, https://doi.org/10.1126/sciadv.abm3468.

    • Search Google Scholar
    • Export Citation
  • Shi, J., C. Tang, Q. Liu, Y. Zhang, H. Yang, and C. Li, 2022: Role of mixed layer depth in the location and development of the Northeast Pacific warm blobs. Geophys. Res. Lett., 49, e2022GL098849, https://doi.org/10.1029/2022GL098849.

    • Search Google Scholar
    • Export Citation
  • Su, J., R. Zhang, X. Rong, Q. Min, and C. Zhu, 2018: Sea surface temperature in the subtropical Pacific boosted the 2015 El Niño and hindered the 2016 La Niña. J. Climate, 31, 877893, https://doi.org/10.1175/JCLI-D-17-0379.1.

    • Search